A few months ago, we implemented support for exception profiling in PHP. One of the key justifications for building this functionality into Continuous Profiler was to show the hidden costs of exceptions in PHP, especially when they are used for flow control in hot code paths. Once this feature was built, we naturally wanted to know if it surfaced these kinds of flow control problems in customer production systems.

We are excited to share a significant update for Grafana Pyroscope users and the broader open source community: the launch of Explore Profiles, a new application that makes it easier and faster to surface meaningful insights from your profiling data. Explore Profiles is a Grafana app plugin designed to integrate seamlessly with Grafana Pyroscope, the open source continuous profiling backend, providing a smooth, queryless experience to browse and analyze your profiling data.

When you face issues like reduced throughput or latency spikes in your production applications, determining the cause isn’t always straightforward. These kinds of performance problems might not arise for simple reasons such as under-provisioned resources; often, the root of the problem lies deep within an application’s runtime execution.

The use of code profiling to troubleshoot application performance can appear daunting to the uninitiated, and many software engineers even assume that this domain is reserved for niche specialists. But here at Datadog, one of the key goals for our Continuous Profiler product has been to take this seemingly intimidating practice of code profiling and make it more accessible to engineers at all levels.

Each day, more than 70 million active users sign into Roblox to create, play, and interact with each other through virtual experiences. And regardless of what those experiences are, exactly — adopting a pet, completing an obstacle course, or fulfilling orders at a virtual pizza parlor — the Roblox observability team is dedicated to making them seamless.

When OpenTelemetry first came into the picture with the merger of OpenCensus and OpenTracing in 2019, it was pretty much all about classic telemetry data, namely- logs, metrics, and traces. Since then, OpenTelemetry has become an indispensable tool in the modern observability landscape. With frequent integrations and introduction to new capabilities every year or so, it has poised itself as an invaluable tool for cloud enterprises.

In today's age of cloud services and SaaS platforms, continuous improvement isn't just a goal — it's a necessity. Here at Elastic, we're always on the lookout for ways to fine-tune our systems, be it our internal tools or the Elastic Cloud service. Our recent investigation in performance optimization within our Elastic Cloud QA environment, guided by Elastic Universal Profiling, is a great example of how we turn data into actionable insights.

Imagine having x-ray vision for your application and seeing exactly what's happening under the hood in real time. That's what thread dumps do for your application—they are a vital component of application performance monitoring (APM) and give you a super-powered peek into its inner workings, helping you spot issues and fix them faster than you can imagine.

Elastic Universal Profiling™ agent is now open source! The industry’s most advanced fleetwide continuous profiling solution empowers users to identify performance bottlenecks, reduce cloud spend, and minimize their carbon footprint. This post explores the history of the agent, its move to open source, and its future integration with OpenTelemetry.

The topic of continuous profiling has been an ongoing discussion in the observability world for some time. I said back in 2021 that profiling was set to be the next major telemetry signal in observability, and in fact, since then there’s been growing interest in profiles. Startups and large observability vendors have gotten into this domain. A significant recent step was when the OpenTelemetry project decided to add profiles to its core signals and formalized the open unified specification for that.